.png){kind=icon}
返回
Efficient optimization of reliability-constrained structural design problems including interval uncertainty
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compstruc.2016.08.004.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A novel interval uncertainty formulation for exploring the impact of epistemic uncertainty on reliability constrained design performance is proposed. An adaptive surrogate modeling framework is developed to locate the lowest reliability value within a multi-dimensional interval. This framework is combined with a multi-objective optimizer, where the interval width is considered as an objective. The resulting Pareto front examines how uncertainty reduces performance while maintaining a specified reliability threshold. Two case studies are presented: a cantilever tube under multiple loads and a composite stiffened panel. The proposed framework demonstrates its ability to resolve the Pareto front in an efficient manner. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Surrogate model
Optimization
Interval uncertainty
Reliability
Composite structures
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.8
论文数:
6.2K
被引数:
1.7W
机构
引用论文
Analysis of stiffened plates under lateral loading using sequential quadratic programming (SQP)
.png){kind=icon}
PREAI
分享收藏分享收藏
Reliability-based design optimization using kriging surrogates and subset simulation使用kriging代理和子集模拟的基于可靠性的设计优化
PREAI
分享收藏Metamodels for computer-based engineering design: survey and recommendations基于计算机的工程设计的元模型: 调查和建议
PREAI
分享收藏
查看更多内容